Identification of a prognostic signature for old-age mortality by integrating genome-wide transcriptomic data with the conventional predictors: the Vitality 90+ Study

ABSTRACT: BACKGROUND: Prediction models for old-age mortality have generally relied upon conventional markers such as plasma-based factors and biophysiological characteristics. However, it is unknown whether the existing markers are able to provide the most relevant information in terms of old-age survival or whether predictions could be improved through the integration of whole-genome expression profiles. METHODS: We assessed the predictive abilities of survival models containing only conventional markers, only gene expression data or both types of data together in a Vitality 90+ study cohort consisting of n = 151 nonagenarians. The all-cause death rate was 32.5% (49 of 151 individuals), and the median follow-up time was 2.55 years. RESULTS: Three different feature selection models, the penalized

ORGANISM(S): Homo sapiens

SUBMITTER: Saara Marttila 

PROVIDER: E-GEOD-65218 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress